DOI: 10.1002/aisy.202100093 Adv. Intell. Syst. 2022, 4, 2100093 In the originally published article, defining of weighting formula in equations (1) and (2) segment similarity (SWS) equation (3) had been presented incorrectly. The authors state that mistakes do not affect related content conclusions study, apologize for any confusion these may have caused.

In many signal processing applications, an appropriate measure to compare two signals plays a fundamental role in both implementing the algorithm and evaluating its performance. Several techniques have been introduced in literature as similarity measures. However, the existing measures are often either impractical for some applications or they have unsatisfactory results in some other applicati...

In many signal processing applications, an appropriate measure to compare two signals plays a fundamental role in both implementing the algorithm and evaluating its performance. Several techniques have been introduced in literature as similarity measures. However, the existing measures are often either impractical for some applications or they have unsatisfactory results in some other applicati...

In this paper, the problem of automatically assigning a piece of traditional Turkish music into a class of rhythm referred to as usul is addressed. For this, an approach for rhythmic similarity measurement based on scale transforms has been evaluated on a set of MIDI data. Because this task is related to time signature estimation, the accuracy of the proposed method is evaluated and compared wi...

2 Distance metrics and similarity measures 2 2.1 Distance metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Vector norm and metric . . . . . . . . . . . . . . . . . . . . . . . 3 2.3 The `p norm and `p metric . . . . . . . . . . . . . . . . . . . . . 3 2.4 Distance metric learning . . . . . . . . . . . . . . . . . . . . . . . 6 2.5 The mean as a similarity measure . . . . . . ...

In this paper, we propose a novel representation of sequences based on the structural information of the sequences. A sequence is represented by a set of rules, which are derived from its subsequences. There are two types of subsequences of interest. One is called frequent pattern, which is a subsequence appearing often enough in the sequence. The other is called correlative pattern, which is a...

A study was r~ade of tile degree of similarity between pairs of Russian nouns, as expressed by their tendency to occur in sentences with identical ~,,ords in identical syntactic relationships. A similarity matrix was prepared for forty nouns; for each pair of nouns the number of shared (i) adjective dependents, (ii) noun dependents, and (iii) noun governors was automatically retrieved from mach...

A novel scheme for securing biometric templates of variable size and order is proposed. The proposed scheme is based on new similarity measure approach, namely the set intersection, which strongly resembles the methodology used in most current state-of-the-art biometrics matching systems. The applicability of the new scheme is compared with that of the existing principal schemes, and it is show...

In this paper we investigate the role of rhythmic similarity as part of melodic similarity in the context of Folksong research. We define a rhythmic similarity measure based on Inner Metric Analysis and apply it to groups of similar melodies. The comparison with a similarity measure of the SIMILE software shows that the two models agree on the number of melodies that are considered very similar...

The notion of exploiting data dependent hypothesis spaces is an exciting new direction in machine learning with strong theoretical foundations[66]. A very practical motivation for these techniques is that they allow us to exploit unlabeled data in new ways [2]. In this work we investigate a particular technique for combining “native” features with features derived from a similarity function. We...